The Groundhog is being developed to line-follow at low altitude and higher speeds. This video is of the field testing taking the speed up to 1.75 m/s. It also explains why the Groundhog now sports sunglasses.

The Track

An oval of 50mm red webbing, bends of radius approx 3m and straights of approx 15m. Testing took place in early morning with glancing sunlight on dew-soaked webbing – great for walking the dog but not so good for computer-vision.

Part of a series of videos and blogs tracking the development of The Groundhog, which was entered into the MAAXX Europe 2017 competition earlier this year.

Having successfully tested the re-written code to follow straight lines using velocity vectors for control and NED space mapping for line detection, we test it around a 50m track comprising 50mm wide red webbing – and we speed it up a bit as well.

The test turned out to be quite successful, with following speeds of 1.5m/s achieved under autonomous control provided by an on-board Raspberry Pi 3. This is significantly faster than the winning UAV in MAAXX Europe this year, which is quite pleasing!

The YouTube video shows both on-board and off-board camera footage, the former demonstrating the roaming regions of interest used by OpenCV to maintain a lock under varying lighting conditions.

Whilst I’m not into FPV, I use an Eachine LCD5800D monitor to check the view from the Raspberry Pi companion computer of The Groundhog. With the super-imposed graphics, it gives a constant view of the status of the image lock on target etc. It also has a nifty built-in recorder.

Recently the link refused to work, and after first replacing the transmitter, I realised it was actually the receiver that had failed. I decided to upgrade the receiver, hopefully fitting a new unit within the existing case.

Several lessons were identified here from the entry of The Groundhog hexacopter in the MAAXX Europe competition earlier this year.

Current developments are around correcting the issues so that we get a UAV successfully lapping the oval track at a minimum average speed of 1m/s.

A number of changes in approach have been made from that previously blogged. Recall the platform is based on a combination of Pixhawk/Raspberry Pi3/OpenCV/Dronekit.

Image analysis:

The birds eye view image transformation in OpenCV was causing segmentation faults on the RPi. Instead the position and bearing of the detected line is calculated using straight trigonometry.

Improvements made to the ranging ROI bands to further speed-up the frame rate. This is now at a reported 50fps (which is faster than the PiCam is supplying them).

Control algorithms:

The use of quaternions has been temporarily suspended in favour of control by velocity vectors.

As in MAAXX Europe, it makes sense to initially test on a straight line. Initial testing was conducted outdoors using red-seatbelt webbing for the line. It was not possible to fly below about 2m as the propwash blew the line away (will sort that next time!).

In this last post of the series I shall overview the main program including the control algorithms for the Groundhog. Code is written in Python, using Dronekit and OpenCV all running on a Raspberry Pi 3.

As we are flying indoors without GPS and also without optical flow, we are using quaternions to control the vehicle in the GUIDED_NOGPS flight mode of ArduCopter. To be honest, I’ve not come across anyone else doing this before, so it must be a good idea…

In this short blog series I’m outlining the hardware and software of The Groundhog, my entry into the recent MAAXX-Europe autonomous drone competition held at the University of the West of England, Bristol.

Connecting the Raspberry Pi 3 to the Pixhawk took quite some working out, so I am hoping that by publishing my own step by step checklist, it may help others save a little time. Continue reading →

In this short blog series I’m outlining the hardware and software of The Groundhog, my entry into the recent MAAXX-Europe autonomous drone competition held at the University of the West of England, Bristol.

In this post I shall overview the approach taken to the image recognition system used to track the line being followed around the track. Remember the line is red, about 50mm across and forms an oval track 20m by 6m. We are attempting to race around as fast as we can, avoiding other UAVs if necessary.